Technical Staff, Infrastructure

Reflection AI
£28,457 - £36,033 a year
City of London, England
Full time
3 weeks ago

Role Overview:

As a member of the technical staff focused on infrastructure at Reflection you will lead the development of a world-class AI research platform, enabling scalable and efficient language model and reinforcement learning training and inference. You will design and implement infrastructure capable of scaling across large GPU clusters and create production-ready inference solutions for cutting-edge AI models. This role offers the opportunity to shape the foundational infrastructure that powers the next generation of AI systems.

Key Responsibilities:

  • Build and optimize large-scale, high-performance AI research infrastructure for Reinforcement Learning (RL).

  • Develop scalable training platforms capable of leveraging tens of thousands of GPUs.

  • Create efficient inference solutions, including vLLM-like platforms for non-LLM models and production-ready serving systems.

  • Collaborate with research teams to align infrastructure capabilities with experimental needs and goals.

  • Maintain a strong focus on performance, scalability, and reliability in all infrastructure components.

Qualifications:

  • Extensive experience building large-scale, high-performance solutions in the AI or software engineering domain.

  • Proficiency in high-performance programming languages such as C++ or Rust.

  • Proven experience building infrastructure at top AI or technology companies.

  • Strong understanding of distributed systems, GPU acceleration, and scalable architectures.

  • A passion for advancing the state of AI research and its real-world applications.

What We Offer:

  • The opportunity to work at the forefront of AI research and infrastructure development.

  • Collaboration with a team of world-class researchers and engineers with experience in groundbreaking projects like ChatGPT, AlphaGo, and Gemini.

  • Competitive compensation and benefits.

How to Apply: If our mission and approach inspire you, and you like working on challenging low-level optimizations to build incredibly efficient infrastructure, we want to hear from you. Consider applying to join the research infrastructure team at Reflection.

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